Instructions to use hf-tiny-model-private/tiny-random-CanineModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-CanineModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-tiny-model-private/tiny-random-CanineModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-CanineModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-CanineModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 657c265dea98a3c7f34482b4529bf63a062fef919e8ad29a7f9b370ad23e91aa
- Size of remote file:
- 4.46 MB
- SHA256:
- 1ab111d99e6aa8444a150ab278fbf3b534e1759faa708f80c541b730c3c9fd98
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